Sökning: "GRAPHS"
Visar resultat 16 - 20 av 304 avhandlingar innehållade ordet GRAPHS.
16. Graph Partitioning and Planted Partitions
Sammanfattning : Graph partitioning is the problem of splitting a graph into two or morepartitions of fixed sizes while minimizing the number of edges that are “cut”.This is an important problem with a wide range of applications in fields suchas VLSI design, parallel processing, bioinformatics, data mining etc. LÄS MER
17. Studies in Efficient Discrete Algorithms
Sammanfattning : This thesis consists of five papers within the design and analysis of efficient algorithms.In the first paper, we consider the problem of computing all-pairs shortest paths in a directed graph with real weights assigned to vertices. We develop a combinatorial randomized algorithm that runs in subcubic time for a special class of graphs. LÄS MER
18. Making Possible by Making Visible : Learning through Visual Representations in Social Science
Sammanfattning : This thesis focuses upon the relationship between teaching and learning of dynamic phenomena and processes in social science and the use of visual representations in social science teaching. Teaching in social science uses many visual representations, such as models, flowcharts and diagrams, in order to help students to grasp phenomena, structures and processes in society. LÄS MER
19. Methods and Algorithms for Data-Intensive Computing : Streams, Graphs, and Geo-Distribution
Sammanfattning : Struggling with the volume and velocity of Big Data has attracted lots of interest towards stream processing paradigm, a paradigm in the area of data-intensive computing that provides methods and solutions to process data in motion. Today's Big Data includes geo-distributed data sources. LÄS MER
20. Statistical Inference of Information in Networks : Causality and Directed Information Graphs
Sammanfattning : Over the last decades, the advancements in measurement, collection, and storage of data have provided tremendous amounts of information. Thus, it has become crucial to extract valuable features and analyze the characteristics of data. As we study more complex systems (e.g. LÄS MER